• C++ Programming for Financial Engineering
    Highly recommended by thousands of MFE students. Covers essential C++ topics with applications to financial engineering. Learn more Join!
    Python for Finance with Intro to Data Science
    Gain practical understanding of Python to read, understand, and write professional Python code for your first day on the job. Learn more Join!
    An Intuition-Based Options Primer for FE
    Ideal for entry level positions interviews and graduate studies, specializing in options trading arbitrage and options valuation models. Learn more Join!

Which Program in the Meantime

functional

Joined
12/3/10
Messages
5
Points
11
Greetings!

I develop exchange connectivity software for a major investment bank. I am located in a western state and probably won't have the opportunity to move to NYC or Chicago for a couple of years. I would ultimately like to develop automated trading algorithms (not simply implement them, but design them). Since I do not have access to a top MBA, MFE, or MSFM program at the moment, I would like to do some education locally in the meantime.

Here are the programs available to me:

1. MS Mathematics (applied and pure)
2. Master of Statistics in Econometrics
3. MS Finance (focus on CFA tests)
4. MS Computational Engineering & Science

Which program do you recommend given my ultimate goal? Why? Note that I still plan to complete an MBA or MSFM after the move in a couple years.

Thanks for your help!
 
are these online programs or a local school? If it's a local school, which one? It would be better to take a look at those programs before we give you any suggestions.
 
For #4, Computational Engineering and Science, the core courses are:

Introduction to Numerical Analysis I
Numerical linear algebra, interpolation, integration, differentiation, approximation (including discrete and continuous least squares, Fourier analysis, and wavelets).

Introduction to Numerical Analysis II
Numerical solution of initial and boundary value problems of ordinary and partial differential equations.

Mathematical Modeling
Development of mathematical models for physical, biological, engineering, and industrial phenomena and problems, using mainly ordinary and partial differential equations. Involvement of analytical and numerical tools suitable for analysis and visualization of the solutions of these problems, including packages such as LINPACK, EISPACK, Maple and Matlab.

Scientific Visualization
Introduction to the techniques and tools needed for the visual display of data. Students will explore many aspects of visualization, using a "from concepts to results" format. The course begins with an overview of the important issues involved in visualization, continues through an overview of graphics tools relating to visualization, and ends with instruction in the utilization and customization of a variety of scientific visualization software packages.
 
A 6th option is Master of Statistics in Mathematics, with the following courses:

Intro to Probability
Statistical Inference I
Statistical Inference II
Linear Models
Multivariate Models
Mathematical Statistics
Stochastic Processes & Simulation I
Stochastic Processes & Simulation II
Time Series
Mathematical Probability
 
Back
Top